Economías de escala en la industria del vino de exportación en Chile

Published by Asociación de Economistas Agrarios de ChileTrans-logarithmic costs, Scale economies, Wine exports., Institutional and Behavioral Economics, Production Economics,

Cloud thermodynamic phase inferred from merged POLDER and MODIS data

International audienceThe global spatial and diurnal distribution of cloud properties is a key issue for understanding the hydrological cycle, and critical for advancing efforts to improve numerical weather models and general circulation models. Satellite data provides the best way of gaining insight into global cloud properties. In particular, the determination of cloud thermodynamic phase is a critical first step in the process of inferring cloud optical and microphysical properties from satellite measurements. It is important that cloud phase be derived together with an estimate of the confidence of this determination, so that this information can be included with subsequent retrievals (optical thickness, effective particle radius, and ice/liquid water content). In this study, we combine three different and well documented approaches for inferring cloud phase into a single algorithm. The algorithm is applied to data obtained by the MODIS (MODerate resolution Imaging Spectroradiometer) and POLDER3 (Polarization and Directionality of the Earth Reflectance) instruments. It is shown that this synergistic algorithm can be used routinely to derive cloud phase along with an index that helps to discriminate ambiguous phase from confident phase cases. The resulting product provides a semi-continuous confidence index ranging from confident liquid to confident ice instead of the usual discrete classification of liquid phase, ice phase, mixed phase (potential combination of ice and liquid particles), or simply unknown phase clouds. This approach is expected to be useful for cloud assimilation and modeling efforts while providing more insight into the global cloud properties derived from satellite data

Computational Cognitive models of Categorization: Predictions under Conditions of Classification Uncertainty

In the category learning literature, similarity models have monopolized a good deal of research. The prototype and exemplar models are both based on the idea that people represent the structure of categories and category instances in the physical world in a mental similarity space. However, evidence for these models comes mainly from paradigms that provide subjects with deterministic feedback (i.e., exemplars belong to their corresponding categories with probability = 1). There is evidence that results obtained with deterministic feedback paradigms may not generalize well under probabilistic feedback conditions (i.e., where exemplars belong to their corresponding categories with probability less than 1). In this current work, we also suggest that probabilistic feedback may better reflect natural conditions, which is another important reason to pursue probabilistic feedback research. Thus, in the current work we set up a category learning experiment with probabilistic feedback and use it to evaluate different models. In addition to the two similarity models discussed above, we also use an associationist model that does not rely on the similarity construct. To compare our three models, we rely on computational modeling, which is a standard way of model comparison in cognitive psychology. Our results show that our associationist model outperforms similarity models on all our model evaluation measures. After presenting our results, we discuss why the similarity-based models fail, and also suggest some future lines of research that are possible using probabilistic feedback procedures

Sedimentology and wine, a cross road

Part of the Alps and the foreland basin will be crossed by our field trip. Limestone, gypsum, landslide siliceous carbonate pebbles and clay, marls carbonates and sandstone are composing the main terroirs of the tasted wines

Comparaison of two levels of laryngeal mask inflation on the occurrence of pharyngeal pain

peer reviewedAfter the insertion of a laryngeal mask (LM), some patients experience pharyngeal pain. To the best of our knowledge, no studies have investigated a possible correlation between ML inflation pressure and postoperative pharyngeal pain. This study aimed to compare postoperative pharyngeal pain, analgesic requirement, and patients’ satisfaction between two groups of ML inflation pressure

Chronic pulmonary fibrosis alters the functioning of the respiratory neural network

Some patients with idiopathic pulmonary fibrosis present impaired ventilatory variables characterised by low forced vital capacity values associated with an increase in respiratory rate and a decrease in tidal volume which could be related to the increased pulmonary stiffness. The lung stiffness observed in pulmonary fibrosis may also have an effect on the functioning of the brainstem respiratory neural network, which could ultimately reinforce or accentuate ventilatory alterations. To this end, we sought to uncover the consequences of pulmonary fibrosis on ventilatory variables and how the modification of pulmonary rigidity could influence the functioning of the respiratory neuronal network. In a mouse model of pulmonary fibrosis obtained by 6 repeated intratracheal instillations of bleomycin (BLM), we first observed an increase in minute ventilation characterised by an increase in respiratory rate and tidal volume, a desaturation and a decrease in lung compliance. The changes in these ventilatory variables were correlated with the severity of the lung injury. The impact of lung fibrosis was also evaluated on the functioning of the medullary areas involved in the elaboration of the central respiratory drive. Thus, BLM-induced pulmonary fibrosis led to a change in the long-term activity of the medullary neuronal respiratory network, especially at the level of the nucleus of the solitary tract, the first central relay of the peripheral afferents, and the Pre-Bötzinger complex, the inspiratory rhythm generator. Our results showed that pulmonary fibrosis induced modifications not only of pulmonary architecture but also of central control of the respiratory neural network

Cloud thermodynamic phase inferred from merged POLDER and MODIS data

The global spatial and diurnal distribution of cloud properties is a key issue for understanding the hydrological cycle, and critical for advancing efforts to improve numerical weather models and general circulation models. Satellite data provides the best way of gaining insight into global cloud properties. In particular, the determination of cloud thermodynamic phase is a critical first step in the process of inferring cloud optical and microphysical properties from satellite measurements. It is important that cloud phase be derived together with an estimate of the confidence of this determination, so that this information can be included with subsequent retrievals (optical thickness, effective particle radius, and ice/liquid water content). In this study, we combine three different and well documented approaches for inferring cloud phase into a single algorithm. The algorithm is applied to data obtained by the MODIS (MODerate resolution Imaging Spectroradiometer) and POLDER3 (Polarization and Directionality of the Earth Reflectance) instruments. It is shown that this synergistic algorithm can be used routinely to derive cloud phase along with an index that helps to discriminate ambiguous phase from confident phase cases. The resulting product provides a semi-continuous index ranging from confident liquid to confident ice instead of the usual discrete classification of liquid phase, ice phase, mixed phase (potential combination of ice and liquid particles), or simply unknown phase clouds. The index value provides simultaneously information on the phase and the associated confidence. This approach is expected to be useful for cloud assimilation and modeling efforts while providing more insight into the global cloud properties derived from satellite data

The Rodrigo & Luz Chronicles: A Composite Counterstory

We provide a composite counter story based on our own experiences grappling with investigating elementary Latinx learners’ experiences and how we have leaned on each other to resist the whiteness of learning to do research in pursuit of a Ph.D. As the counterstory shows, we collectively worked together to write our own continuations of the story between Rodrigo, a graduate research assistant on a project about Latinx learners’ experiences, and Luz, a 4th grade Latina learner who is participating in the study. Together, we supported each other to use storytelling to challenge dominant narratives of the relationship between researcher and researched. Our hope is that this counterstory helps others to reflect on and explore issues of assimilation and provides them permission to challenge how we do research